This paper deals with the relationship between knowledge, innovation and regional growth. The study is carried out through the application of nonparametric estimation methods to European data at NUTS2 level. We provide evidence that the share of innovative ...firms plays a more relevant role in...

This paper analyzes the determinants of regional economic growth in the European Union. The nonparametric approach adopted allows us not only to uncover their relevance but also to determine whether or not they exert a linear in uence. We obtain evidence of a nonlinear relationship between...

This paper analyses region-level technical efficiency in the European Union over the 1995 to 2007 period. We propose the application of a nonparametric conditional frontier methodology to account for the presence of geographical externalities that are beyond the control of regional authorities....

We propose a semi-parametric spatial auto-covariance specification of the growth model to examine the growth behaviour of European regions in the period 1988-2000. This specification simultaneously takes account of the problems of non-linearities and spatial dependence. We obtain two main...

The paper uses nonparametric methodology to examine the role of institutions in understanding differential levels of development across countries. This technique estimates first order derivatives for every country allowing a deeper look into the impact of institutions on development. The...

The paper uses nonparametric methodology to examine the role of institutions in understanding differential levels of development across countries. By using the Li-Racine (2004) generalized kernel estimation methodology, our paper allows a deeper look into the impact of institutions on...

We propose a nonparametric test that distinguishes 'depressions' and 'booms' from ordinary recessions and expansions. Depressions and booms are defined as coming from another underlying process than recessions and expansions. We find four depressions and booms in the NBER business cycle between...

High-dimensional regression problems which reveal dynamic behavior are typically analyzed by time propagation of a few number of factors. The inference on the whole system is then based on the low-dimensional time series analysis. Such highdimensional problems occur frequently in many different...

We consider two semiparametric models for the weight function in a bias sample model. The object of our interest parametrizes the weight function, and it is either Euclidean or non Euclidean. One of the models discussed in this paper is motivated by the estimation the mixing distribution of...